The present invention relates generally to intensity modulated radiation therapy (IMRT) and in particular to the selection of beam orientations by evaluating each beamlet of the beam at various gantry angles prior to treatment.
The goal of radiation therapy is to deliver a prescribed dose of radiation usually in the form of electromagnetic radiation (photons), electrons, neutrons or protons to a treatment target, such as a tumor, while sparing adjacent organs at risk (OARs). Intensity modulated radiation therapy (IMRT) adds a new degree of freedom to the conventional three-dimensional radiation therapy and allows one to achieve a better dose distribution by modulating the intensity profiles of the incident beams. For general information on IMRT the reader is referred to T. Bortfield, et. al, xe2x80x9cX-ray Field Compensation with Multileaf Collimatorsxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 28, 1994, pp. 723-730; T. R. Mackie, et al., xe2x80x9cTomotherapyxe2x80x9d, Seminars on Radiation Oncology, Vol. 9, 1999, pp. 108-117; C. C. Ling, et al., xe2x80x9cConformal Radiation Treatment of Prostate Cancer using Inversely-Planned Intensity Modulated Photon Beams Produced with Dynamic Multileaf Collimationxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 35 (1996), pp. 721-730.
In IMRT treatment planning the angles at which radiation is delivered to the treatment site in the patient""s body, commonly called gantry angles and couch angles in the case of non-coplanar beams, are usually pre-selected based on experience and intuition of the operator. The corresponding beam intensity profiles are then optimized under the guidance of an objective function using so-called inverse treatment planning methods. General information on these methods is provided by S. Webb, xe2x80x9cOptimizing the Planning of Intensity-Modulated Radiotherapyxe2x80x9d, Physics in Medicine and Biology, Vol. 39, 1994, pp. 2229-2246; S. V. Spirou and C. S. Chui, xe2x80x9cA Gradient Inverse Planning Algorithm with Dose-Volume Constraintsxe2x80x9d, Medical Physics, Vol. 25, 1998, pp. 321-333; R. Mohan, et al., xe2x80x9cThe Potential and Limitations of the Inverse Radiotherapy Techniquesxe2x80x9d, Radiotherapy and Oncology, Vol. 32, 1994, pp. 232-248; L. Xing, et al., xe2x80x9cFast Iterative Algorithms for 3D Inverse Treatment Planningxe2x80x9d, Medical Physics, Vol. 25, 1998, pp. 1845-1849; and L. Xing and G. T. Y. Chen, xe2x80x9cIterative Methods for Inverse Treatment Planningxe2x80x9d, Physics in Medicine and Biology, Vol. 41, 1996, pp. 2107-2123.
The prior art teaches numerous approaches to beam orientation selection in conventional radiation therapy and in IMRT. For information on the methods investigated for conventional radiation therapy the reader is referred to the following references: S. Soderstrom, et al., xe2x80x9cWhich is the Most Suitable Number of Photon Beam Portals in Coplanar Radiation Therapyxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 33, 1995, pp. 151-159; G. A. Ezzell, xe2x80x9cGenetic and Geometric Optimization of Three-Dimensional Radiation Therapy Treatment Planningxe2x80x9d, Medical Physics, Vol. 23, 1996, pp. 293-305; P. Gokhale, et al., xe2x80x9cDetermination of Beam Orientations in Radiotherapy Planningxe2x80x9d, Medical Physics, Vol. 21, 1994, pp. 393-400; M. E. Hosseini-Ashrafi, et al., xe2x80x9cPre-optimization of Radiotherapy Treatment Planning: An Artificial Neural Network Classification Aided Techniquexe2x80x9d, Physics in Medicine and Biology, Vol. 44, 1999, pp. 1513-1528; C. G. Rowbottom, et al., xe2x80x9cBeam Orientation Customization using an Artificial Neural Networkxe2x80x9d, Physics in Medicine and Biology, Vol. 44, 1999, pp. 2251-2262; B. C. J. Cho, et al., The Development of Target-Eye-View Maps for Selection of Coplanar or Noncoplanar Beams in Conformal Radiotherapy Treatment Planningxe2x80x9d, Medical Physics, Vol. 26, 1999, pp. 2367-2372; S. K. Das, et al., xe2x80x9cSelection of Coplanar or Noncoplanar Beams using Three-dimensional Optimization Based on Maximum Beam Separation and Minimized Non-Target Irradiationxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 38, 1997, pp. 643-655; D. L. McShan, et al., xe2x80x9cAdvanced Interactive Planning Techniques for Conformal Therapy: High Level Beam Description and Volumetric Mapping Techniquesxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 33, 1995, pp. 1061-1072; C. G. Rowbottom, et al., xe2x80x9cConstrained Customization of Noncoplanar Beam Orientations in Radiotherapy of Brain Tumorsxe2x80x9d, Physics in Medicine and Biology, Vol. 44, 1999, pp. 383-399; S. L. Sailer, et al., xe2x80x9cThe Tetrad and Hexad: Maximum Beam Separation as a Starting Point for Noncoplanar 3D Treatment Planning: Prostate Cancer as a Test Casexe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 30, 1994, pp. 439-446; G. T. Y. Chen, et al., xe2x80x9cThe use of Beam""s Eye View Volumetrics in the Selection of Noncoplanar Radiation Portalsxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 23, 1992, pp. 153-163; H. -M. Lu, et al., xe2x80x9cOptimized Beam Planning for Linear Accelerator-Based Stereotactic Radiosurgeryxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 39, 1997, pp. 1183-1189; M. Goitein, et al., xe2x80x9cMulti-dimensional Treatment Planning: II. Beam""s Eye-View, Back Projection, and Projection through CT Sectionsxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 9, 1983, pp. 789-797; and Carl Graham, et al., xe2x80x9cImprovements in Prostate Radiotherapy from the Customization of Beam Directionsxe2x80x9d, Medical Physics, Vol. 25, 1998, pp. 1171-1179.
Beam orientation selection in IMRT is discussed in the following references: J. Stein, et al., xe2x80x9cNumber and Orientations of Beams in Intensity-Modulated Radiation Treatmentsxe2x80x9d, Medical Physics, Vol. 24, 1997, pp. 149-160; M {dot over (A)}sell, et al., xe2x80x9cOptimal Electron and Combined Electron and Photon Therapy in the Phase Space of Complication-Free Curexe2x80x9d, Physics in Medicine and Biology, Vol. 44, 1999, pp. 235-252; T. Bortfield and W. Schlegel, xe2x80x9cOptimization of Beam Orientations in Radiation Therapy: Some Theoretical Considerationsxe2x80x9d, Physics in Medicine and Biology, Vol. 38, 1993, pp. 291-304; A. Pugachev, et al., xe2x80x9cBeam Orientations in IMRT: To Optimize or not to Optimize?xe2x80x9d, The Use of Computers in Radiation Therapy, XIII ICCR, 2000, pp. 37-39; S. Soderstrom and A. Brahme, xe2x80x9cSelection of Suitable Beam Orientations in Radiation Therapy using Entropy and Fourier Transform Measuresxe2x80x9d, Physics in Medicine and Biology, Vol. 37, 1992, pp. 911-924; A. Pugachev, A. Boyer, L. Xing, xe2x80x9cBeam Orientation Optimization in Intensity-Modulated Radiation Treatment Planningxe2x80x9d, Medical Physics, Vol. 27, 2000, pp. 1238-1245; and M. Braunstein, et al., xe2x80x9cOptimum Beam Configurations in Tomographic Intensity Modulated Radiation Therapyxe2x80x9d, Physics in Medicine and Biology, Vol. 45, 2000, pp. 305-328.
Unfortunately, there exists a complex interdependence or coupling between the gantry angles and the beam intensity profiles. In principle, all one needs to do is to add the gantry angle variables into an objective function and then to optimize the objective function with respect to the gantry angles and the beamlet weights. In practice, this brute-force optimization is computationally intensive and hence not very useful because the search space constituted by gantry angles and the beamlet weights cannot be separated into two independent subspaces because of the coupling mentioned above. In addition, the objective function is a non-convex function of the gantry angles and a stochastic sampling of the gantry angles has to be used to avoid trapping in a local minimum. Consequently, computation time required by a complete optimization becomes prohibitively long, making impractical the use of beam orientation optimization for routing clinical applications.
Due to the above-mentioned obstacles, typical IMRT procedures typically involve choosing xe2x80x9coptimalxe2x80x9d gantry angles first. Then, the beam intensity profiles are optimized. The influence of a set of gantry angles on the final radiation dose distribution in the patient""s body is not known until the beam intensity profile optimization is performed. Trial and error attempts are often needed in order to determine a set of good gantry angles for IMRT treatment.
In U.S. Pat. No. 6,260,005 B1 Yang et al. describe an optimization method for arbitrary assessment criteria which can be applied to IMRT beamlet weight optimization and dose calculation. However, just like any other existing systems, no automated or semi-automated computational tool is available for the beam orientation selection. In order to use their system to simulate a radiation treatment generate a treatment plan, it is required that the user to pre-determine the directions of the incident beams and the beam energy before beamlet optimization.
Beam""s eye view (BEV) technique was originally used in 3D treatment planning as an interactive tool to assist the oncologists to define radiation portal entry angles that exclude critical structures while fully encompassing the target volume. The binary beam orientation scoring was further improved by the introduction of BEV volumetrics (G. T. Y. Chen, et al., xe2x80x9cThe use of Beam""s Eye View Volumetrics in the Selection of Noncoplanar Radiation Portalsxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 23, 1992, pp. 153-163; D. L. McShan, et al., xe2x80x9cAdvanced Interactive Planning Techniques for Conformal Therapy: High Level Beam Description and Volumetric Mapping Techniquesxe2x80x9d, International Journal of Radiation Oncology, Biology, Physics, Vol. 33, 1995, pp. 1061-1072). In this approach, the volume of normal structures intercepted by a specified aperture/portal direction is calculated for all possible incident directions, permitting the planer to evaluate quantitatively the relative merit of a given field direction. In this approach the good beam directions are those minimizing the volume of normal tissue intercepted. While the technique works well for conventional 3D radiation therapy, radical modifications must be made for it to be suitable for IMRT. The problem that we are dealing with now is quite different. The portal shape of each segment and its fractional weight are completely determined by the inverse planning algorithm.
Generally speaking, an intensity modulated beam which intercepts a large volume of sensitive structure(s) is not necessarily a bad beam because of the possibility of partial transmission of part of the incident beam. In reality, it is the dose and/or dose-volume that determines the damage to a sensitive structure (for biology based model, similar technique can be constructed along the line here). Recently Rowbottom et al (C. G. Rowbottom, et al., xe2x80x9cConstrained Customization of Noncoplanar Beam Orientations in Radiotherapy of Brain Tumorsxe2x80x9d, Physics in Medicine and Biology, Vol. 44, 1999, pp. 383-399) have constructed beam orientation cost function based on beam volumetrics and simple dose model for conventional radiation therapy. In their model, they computed the doses delivered to the target volume and sensitive structures by a uniform-beam with constant weight from each direction. Because there are usually multiple structures intercepting the beam from a given direction, they introduced an empirical trade-off factor to weight each structure to come up with an overall score for each direction. The use of the trade-off factors introduce a great subjectivity into the beam orientation scoring and renders the approach unsuitable for beam orientation selection in IMRT or even in conventional radiation therapy. The underlying shortcoming of the approach is that it did not consider a priori dosimetric knowledge of the system (note that the BEV volumetrics approach is essentially based on a priori geometric information of the system).
Clearly, simple tools and intelligent searches are required in order to provide clinically practical tools for beam orientation selection. Unfortunately, none of the prior art approaches have been able to effectively overcome the challenge of determining optimal gantry angles and beam profiles in a manner that is clinically useful.
It is therefore a primary object of the present invention to provide a method for selecting beam orientations for intensity modulated radiation therapy in a manner that does not require excessive computational effort. The method that we wish to construct is a computational method that decouples the fluence profile (the portal and fractional weight of the segments) design and the selection of beam orientation.
Furthermore, it is an object of the invention to provide a method for scoring and selecting gantry angles in a manner which is simple and easy to implement in the clinical environment.
In our technique, the merit of a beam direction should be measured by what that beam could achieve dosimetrically without exceeding the dosimetric or dose-volume constraint of the system. Furthermore, the best achievable scenario of a given beam could be determined based on the a priori dosimetric and geometric information of the given patient.
These and other objects and advantages of the invention will become apparent upon further reading of the specification.
The objects and advantages are achieved by a method for selecting an orientation of a treatment beam for intensity modulated radiation therapy based on analysis performed on a model of a patient geometry prior to the actual treatment. The model of patient geometry includes a planning target volume (PTV) containing the object to be treated by radiation, e.g., a tumor, and the structure or structures at risk, such as internal organs, bone and/or tissue. The method calls for assigning a tolerance parameter to the structure or structures at risk, subdividing the treatment beam into beamlets, selecting a treatment parameter and selecting a set of angles or orientation for the treatment beam. These orientations typically include gantry angles and couch angles. In the next step, a score is derived for each of the angles in the set by weighting each of the beamlets so as to maximize the treatment parameter in the PTV while not exceeding the tolerance parameter in the structure or structures at risk at each gantry angle. The derived scores are used to construct a scoring function which is essentially the score charted as a function of angle. Based on the scoring function one or more angles are selected as treatment angle(s) to be used during the actual radiation treatment.
In a preferred embodiment, the treatment parameter is a radiation dose. Thus, it is the radiation dose delivered to the PTV which is maximized for each beamlet. The tolerance parameter is also a radiation dose, specifically a tolerance dose for the structure or structures at risk. The various structures at risk, i.e., internal organs, bones and other tissue will each have an associated tolerance dose.
In an alternative embodiment the treatment parameter is an energy rather than radiation dose. In this case the tolerance parameter is still tolerance dose.
In one embodiment the cross section of the beamlets is adjusted in deriving the score. For example, if the beamlets have square beam cross sections, they cay be rotated (collimator rotation). This is done to maximize the treatment parameter, e.g., radiation dose, delivered to the PTV while not exceeding the tolerance parameter in the structure or structures at risk.
It is convenient to divide the model of the patient into voxels and derive the score for each beamlet in each voxel. Preferably, the entire PTV is broken up into voxels and thus the score is obtained for each voxel in the PTV. For example, the score can include computing for the voxels an empiric score Si:             S      i        =                  1                  N          T                    ⁢                        ∑                      n            ∈            target                          ⁢                              (                                          d                ni                                            D                T                P                                      )                    2                      ,
where dni is the radiation dose delivered to voxel n by beamlet i, NT is the number of voxels in the PTV, and DTP is a prescribed radiation dose.
In one embodiment the method involves calculating a ratio by which the intensity of each beamlet has to be reduced to not exceed the tolerance parameter in the one or more structures at risk. In this case the tolerance parameter is preferably a radiation dose. The limiting value for this radiation dose is typically dictated by many factors, including prior radiation exposure and other considerations known to a person skilled in the art.
As will be apparent to a person skilled in the art, the invention admits of a large number of embodiments and versions. The below detailed description and drawings serve to further elucidate the principles of the invention and some of its embodiments.